volume | PIER Journals

Abstract

In the final step of any filter design process, the desired center frequency, coupling factor and external quality factor (Q_ext) are used to determine the physical parameters of the filter. Although in the most cases the physical dimensions of a single resonator for a given center frequency are determined using exact analytical or simple approximate equations, usually such simple equations cannot be found to easily relate the required coupling factor and Q_ext to the physical parameters of the filter. Analytical calculation of coupling factor and Q_ext versus dimensions are usually complicated due to the geometrical complexities or in some cases such as microstrip resonators due to the lack of exact solution for the field distribution. Therefore coupling factor and Q_ext of various kinds of resonators, especially microstrip resonators, are related to the physical parameters of the structure by the use of time consuming full wave simulations. In this paper a surprisingly fast and completely general approach based on a soft computing pattern-based processing technique, called active learning method (ALM) is proposed to overcome the time consuming process of coupling factor and Q_ext determination. At first the ALM technique and the steps of modeling are generally described, then as an example and in order to show the ability of the method this modeling approach is implemented to model the coupling factor and Q_ext surfaces of microstrip open-loop resonators versus physical parameters of the structure. Using the ALM-based extracted surfaces for coupling factor and Q_ext, two four pole Chebychev bandpass filters are designed and fabricated. Good agreement between the measured and simulated results validates the accuracy of the proposed approach.

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Dr. Payman Rezaee

Dr. Majid Tayarani

Prof. Reinhard Knöchel